In previous work, we have developed, deployed and evaluated a highly novel intelligent training system for diagnosing and reporting on cases of melanoma and other melanocytic lesions. Results show that the system is highly effective in improving student performance. We propose to take the lessons learned in the past funding period, to transform our current system from an isolated standalone system in one institution and one domain, into a distributed general tutoring environment that functions across multiple institutions. The distributed architecture we will propose will provide a means to address some of the most important current barriers in providing effective cancer education - the expense and cost of content development, the isolated nature of most educational systems, and the difficulty of supporting effective collaboration between institutions. In order to accomplish these goals, we will (1) link the system to standardized vocabularies and data standards being developed at NCI as a method to extend the domain from one small area of Pathology to all areas of Pathology, (2) develop authoring environments that allow individuals outside of our institution to use our systems to create and deploy their own tutoring cases resulting in a national network of tutored pathology cases, and (3) integrate the system with clinical information systems and workflows so that all of the highly annotated clinical materials become available as teaching material with minimal further work. The result of this project will be a nationally networked intelligent tutoring system that provides a platform for standards based education within an entire domain.